In the prior art, lossy compression is usually applied to a coding process, and within the same compressing standard, the bigger the compression ratio is, the larger the loss is. Thus decoding quality which is finally presented in a code stream compressed totally depends on compression methods and parameters used in the coding process.
In order to improve decoding quality of images or videos, mathematical algorithms are used to compensate lost pixels in lossy compression in the prior art. However, if an excellent decoding effect is desired, those mathematical algorithms are usually very complicated, and the computing requirement of the decoding side is very high, so that it is not practically applied. Moreover, since the essence of this method is estimating loss by using limited information of original images or videos, in this situation, the decoding effect will not be very good for those images or videos with poor quality.
Therefore, a new decoding method and decoder with lower computing complexity is required to improve decoding quality of various images or videos.